BACKGROUND:Psoriasis is a chronic, immune-mediated inflammatory skin disease. Screening skin metabolites could unravel the pathophysiology of psoriasis and provide new diagnostic approaches. Due to the lack of suitable methodologies for collecting scarce amounts of skin excretions, the psoriatic skin metabolome has not been extensively studied.

Ambient ionization mass spectrometry (AIMS) has grown into a group of emerging analytical techniques that allow rapid, real-time, high-throughput, in situ, and in vivo analysis in many scientific fields including biomedicine, pharmaceuticals, and forensic sciences. While dozens of AIMS techniques have been introduced over the past two decades, their broad commercial and industrial use is still restricted by multiple challenges. In this Perspective, we discuss the most relevant technical challenges facing AIMS, i.e., reproducibility, quantitative ability, molecular coverage, sensitivity, and data complexity, and scientists' recent attempts to overcome these hurdles. Furthermore, we present future directions of AIMS from our perspective, including the necessity that efforts should be made to unravel blind biomolecules in routine analysis, the construction of a data depository for AIMS users, the full automation of pipelines for prospect integration in a robotic laboratory, the movement toward on-site tests, and the expansion of outreach to motivate government officials in policymaking. We anticipate that, with progress in these critical but immature areas, AIMS technology will keep evolving to become a more robust and user-friendly set of technologies and, consequently, be translated into everyday life practice.

Metabolites excreted by skin have a huge potential as disease biomarkers. However, due to the shortage of convenient sampling/analysis methods, the analysis of sweat has not become very popular in the clinical setting (pilocarpine iontophoresis being a prominent exception). In this report, a facile method for sampling and rapid chemical profiling of skin metabolites excreted with sweat is proposed. Metabolites released by skin (primarily the constituents of sweat) are collected into hydrogel (agarose) micropatches. Subsequently, they are extracted in an online analytical setup incorporating nanospray desorption electrospray ionization and an ion trap mass spectrometer. In a series of reference measurements, using bulk sampling and electrospray ionization mass spectrometry, various low-molecular-weight metabolites are detected in the micropatches exposed to skin. The sampling time is as short as 10 min, while the desorption time is 2 min. Technical precision of micropatch analysis varies within the range of 3-42%, depending on the sample and the method of data treatment; the best technical precision (≤10%) has been achieved while using an isotopically labeled internal standard. The limits of detection range from 7 to 278 pmol. Differences in the quantities of extracted metabolites are observed for the samples obtained from healthy individuals (intersubject variabilities: 30-89%; n = 9), which suggests that this method may have the potential to become a semiquantitative assay in clinical analysis and forensics.

Cholesterol is an important lipid molecule in cell membranes and lipoproteins. Cholesterol is also a precursors of steroid hormones, bile acids, and vitamin D. Abnormal levels of cholesterol or its precursors have been observed in various human diseases, such as heart diseases, stroke, type II diabetes, brain diseases and many others. Therefore, accurate quantification of cholesterol is important for individuals who are at increased risk for these diseases. Multiple analytical methods have been developed for analysis of cholesterol, including classical chemical methods, enzymatic assays, gas chromatography (GC), liquid chromatography (LC), and mass spectrometry (MS). Strategy known as ambient ionization mass spectrometry (AIMS), operating at atmospheric pressure, with only minimal sample pretreatments for real time, in situ , and rapid interrogation of the sample has also been employed for quantification of cholesterol. In this review, we summarize the most prevalent methods for cholesterol quantification in biological samples and foods. Nevertheless, we highlight several new technologies, such as AIMS, used as alternative methods to measure cholesterol that are potentially next-generation platforms. Representative examples of molecular imaging of cholesterol in tissue sections are also included in this review article.